A research paper computes a p-value of 0.45. How would you interpret this p-value?
All infants born in the state of Missouri during the 1995 calendar year who have one or more visits to the Emergency room during their first year of life.
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A research paper computes a p-value of 0.45. How would you interpret this p-value?
Figure 1: xkcd cartoon about jelly beans and cancer
Figure 2: Figure 2. Cartoon showing interpretation of various p-values
General form of standardization
Specific standardization for the mean
\(P[-t(\alpha/2; n-1) < \frac{\bar{X}-\mu}{se(\bar{X})} < t(\alpha/2; n-1)] = 1-\alpha\)
\(P[-t(\alpha/2; n-1)se(\bar{X}) < \bar{X}-\mu < t(\alpha/2; n-1)se(\bar{X})] = 1-\alpha\)
\(P[\bar{X}-t(\alpha/2; n-1)se(\bar{X}) < \mu < \bar{X} + t(\alpha/2; n-1)se(\bar{X})] = 1-\alpha\)
If n > 30
If n < 30, we have 1-\(\alpha\) level of confidence that the population mean lies between
If n > 30, we have 1-\(\alpha\) level of confidence that the population mean lies between
Figure 3: Excerpt from Mondal 2023
Figure 4: Table 1 from Mondal 2023
This file was downloaded from the DASL (Data and Story Library) website. There are no details about who created the data set or what permissions are allowed. Educational uses of this data are probably allowed under the Fair Use provisions of U.S. Copyright Law.
This is a tab delimited data file. There are 50 rows and 2 columns of data.
The first variable is the sample number (1 to 50). The second variable is the circumference of the baseball in inches. The variable names are included at the top of the data.
The first variable is the sample number (1 to 50). The second variable is the circumference of the baseball in inches. The variable names are included at the top of the data.
The standard sized baseball, according to Wikipedia and other sources on the Internet is 9 to 9.25 inches. There are no missing values in this data set.
This data dictionary was written by Steve Simon on 2023-09-10 and is placed in the public domain.
Please be sure to skip past this documentation while importing the data.
Figure 5: SPSS import dialog box
Figure 6: SPSS one-sample t-test dialog box
Figure 7: SPSS one-sample t-test output (1/3)
\(\ \)
Check that \(\frac{0.049415}{\sqrt{50}}=0.006988\).
Figure 8: SPSS one-sample t-test output (2/3)
\(\ \)
Check that \(\frac{9.11754-9.125}{0.006988}=-1.068\).
Figure 9: SPSS one-sample t-test output (3/3)
Check that \(\frac{9.11754-9.125}{0.049415}=-0.151\).
This file is included as part of the base package of R and was converted by Steve Simon to a text file. There are no details about who created the data set. The code for R is published under an open source license, and the datasets included with R are presumably covered by the same license.
This is a tab delimited data file. There are 15 rows and 3 columns of data.
The first variable is the sample number (1 to 15). The second variable is the height of an adult female (inches). The third variable is the weight (pounds). The variable names are not included at the top of the data.
This data dictionary was written by Steve Simon on 2023-09-10 and is placed in the public domain.
Please be sure to skip past this documentation while importing the data.
Figure 10: SPSS data after importing
Figure 11: SPSS data after variable name change
Figure 12: SPSS dialog box for converting from inches to meters
Figure 13: SPSS dialog box for converting from pounds to kilograms
Figure 14: SPSS dialog box for BMI
Select Analyze | Compare Means and Proportions | One-sample T Test from the SPSS menu.
Figure 15: SPSS dialog box for one-sample t-test
Figure 16: SPSS output from one-sample t-test (1/3)
Figure 17: SPSS output from one-sample t-test (2/3)
Figure 18: SPSS output from one-sample t-test (3/3)